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» Approximation Methods for Supervised Learning
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NIPS
2000
15 years 1 months ago
A New Approximate Maximal Margin Classification Algorithm
A new incremental learning algorithm is described which approximates the maximal margin hyperplane w.r.t. norm p 2 for a set of linearly separable data. Our algorithm, called alm...
Claudio Gentile
73
Voted
ICML
2002
IEEE
16 years 1 months ago
Univariate Polynomial Inference by Monte Carlo Message Length Approximation
We apply the Message from Monte Carlo (MMC) algorithm to inference of univariate polynomials. MMC is an algorithm for point estimation from a Bayesian posterior sample. It partiti...
Leigh J. Fitzgibbon, David L. Dowe, Lloyd Allison
101
Voted
ICML
2003
IEEE
16 years 1 months ago
Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic
When the goal is to achieve the best correct classification rate, cross entropy and mean squared error are typical cost functions used to optimize classifier performance. However,...
Lian Yan, Robert H. Dodier, Michael Mozer, Richard...
ACCV
2007
Springer
15 years 6 months ago
Analyzing Facial Expression by Fusing Manifolds
Feature representation and classification are two major issues in facial expression analysis. In the past, most methods used either holistic or local representation for analysis. ...
Wen-Yan Chang, Chu-Song Chen, Yi-Ping Hung
108
Voted
IJON
2010
152views more  IJON 2010»
14 years 11 months ago
Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data
Due to the tremendous increase of electronic information with respect to the size of data sets as well as their dimension, dimension reduction and visualization of high-dimensiona...
Kerstin Bunte, Barbara Hammer, Axel Wismüller...